scholarly journals Quantitative study of the influence of organic-rich and natural fracture-rich regions on shale gas production

2020 ◽  
Vol 570 ◽  
pp. 042041
Author(s):  
S M Wei ◽  
Y Jin ◽  
Y Xia ◽  
Y Q Zhang
Keyword(s):  
Quantitative Study ◽  
Shale Gas ◽  
Gas Production ◽  
Natural Fracture

Quantitative Prediction of Radon Concentration at Wellhead in Shale Gas Development

SPE Journal ◽  
2016 ◽  
Vol 22 (01) ◽  
pp. 235-243 ◽  
Author(s):  
Wei Tian ◽  
Xingru Wu ◽  
Tong Shen ◽  
Zhenyu Zhang ◽  
Sumeer Kalra
Keyword(s):  
Natural Gas ◽  
Numerical Simulations ◽  
Shale Gas ◽  
Radon Concentration ◽  
Marcellus Shale ◽  
Gas Production ◽  
Influential Factors ◽  
Natural Fracture ◽  
Quantitative Prediction ◽  
Radon Gas

Summary Hydraulic fracturing has been applied as an effective method to increase gas production from shale formations; however, this method has also raised concerns about its adverse impacts on environment. For example, in the Marcellus shale formation, some measured radon-gas concentrations exceeded the safe standard. Therefore, it is important to quantitatively evaluate radon concentration from fractured wells. However, existing researches have not successfully conducted a systematic and predictive study on the relationship between shale gas production and radon concentration at the wellhead of a hydraulically fractured well. To address this issue and quantitatively determine the radon concentration, we present the mechanisms of radon-gas generation and releasing, and conducted numerical simulations on its transport process in the subsurface formation system. The concentration of radon in produced gas is related with the original sources where the natural gas is extracted. Radon, generated from the radium alpha decay process, is trapped in pore spaces before the reservoir development. With the fluid flowing through the subsurface network, released radon will move to surface with the produced streams such as natural gas and flowback water. Our study shows that the radon concentration at wellhead could be significant. Influential factors such as natural-fracture-network properties, formation petrophysical parameters, and fracture dimension are investigated with sensitivity studies through numerical simulations. Analysis results suggest that radon wellhead concentration is strongly related with production rate. Thus, careful production design and protection are necessary to reduce radon hazard regarding the public and environmental impact.

scholarly journals Triple-Porosity Modelling for the Simulation of Multiscale Flow Mechanisms in Shale Reservoirs

Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mingyao Wei ◽  
Jishan Liu ◽  
Derek Elsworth ◽  
Enyuan Wang
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Gas Transport ◽  
Gas Production ◽  
Natural Fracture ◽  
System Matrix ◽  
Fracture Permeability ◽  
Gas Reservoir ◽  
Apparent Permeability ◽  
Shale Reservoir

Shale gas reservoir is a typical type of unconventional gas reservoir, primarily because of the complex flow mechanism from nanoscale to macroscale. A triple-porosity model (M3 model) comprising kerogen system, matrix system, and natural fracture system was presented to describe the multispace scale, multitime scale, and multiphysics characteristic of gas flows in shale reservoir. Apparent permeability model for real gas transport in nanopores, which covers flow regime effect and geomechanical effect, was used to address multiscale flow in shale matrix. This paper aims at quantifying the shale gas in different scales and its sequence in the process of gas production. The model results used for history matching also showed consistency against gas production data from the Barnett Shale. It also revealed the multispace scale process of gas production from a single well, which is supplied by gas transport from natural fracture, matrix, and kerogen sequentially. Sensitivity analysis on the contributions of shale reservoir permeability in different scales gives some insight as to their importance. Simulated results showed that free gas in matrix contributes to the main source of gas production, while the performance of a gas shale well is strongly determined by the natural fracture permeability.

scholarly journals Analysis of the Influencing Factors on the Well Performance in Shale Gas Reservoir

Geofluids ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Cheng Dai ◽  
Liang Xue ◽  
Weihong Wang ◽  
Xiang Li
Keyword(s):  
Shale Gas ◽  
Gas Flow ◽  
Gas Production ◽  
Recovery Factor ◽  
Natural Fracture ◽  
Total Production ◽  
Gas Reservoir ◽  
Free Gas ◽  
Shale Gas Reservoir ◽  
Adsorbed Gas

Due to the ultralow permeability of shale gas reservoirs, stimulating the reservoir formation by using hydraulic fracturing technique and horizontal well is required to create the pathway of gas flow so that the shale gas can be recovered in an economically viable manner. The hydraulic fractured formations can be divided into two regions, stimulated reservoir volume (SRV) region and non-SRV region, and the produced shale gas may exist as free gas or adsorbed gas under the initial formation condition. Investigating the recovery factor of different types of shale gas in different region may assist us to make more reasonable development strategies. In this paper, we build a numerical simulation model, which has the ability to take the unique shale gas flow mechanisms into account, to quantitatively describe the gas production characteristics in each region based on the field data collected from a shale gas reservoir in Sichuan Basin in China. The contribution of the free gas and adsorbed gas to the total production is analyzed dynamically through the entire life of the shale gas production by adopting a component subdivision method. The effects of the key reservoir properties, such as shale matrix, secondary natural fracture network, and primary hydraulic fractures, on the recovery factor are also investigated.

scholarly journals New Hybrid Approach for Developing Automated Machine Learning Workflows: A Real Case Application in Evaluation of Marcellus Shale Gas Production

Fuels ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 286-303
Author(s):  
Vuong Van Pham ◽  
Ebrahim Fathi ◽  
Fatemeh Belyadi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Shale Gas ◽  
Field Data ◽  
Marcellus Shale ◽  
Hybrid Approach ◽  
Gas Production ◽  
Bayesian Optimization ◽  
Real Field ◽  
Engineering Problems

The success of machine learning (ML) techniques implemented in different industries heavily rely on operator expertise and domain knowledge, which is used in manually choosing an algorithm and setting up the specific algorithm parameters for a problem. Due to the manual nature of model selection and parameter tuning, it is impossible to quantify or evaluate the quality of this manual process, which in turn limits the ability to perform comparison studies between different algorithms. In this study, we propose a new hybrid approach for developing machine learning workflows to help automated algorithm selection and hyperparameter optimization. The proposed approach provides a robust, reproducible, and unbiased workflow that can be quantified and validated using different scoring metrics. We have used the most common workflows implemented in the application of artificial intelligence (AI) and ML in engineering problems including grid/random search, Bayesian search and optimization, genetic programming, and compared that with our new hybrid approach that includes the integration of Tree-based Pipeline Optimization Tool (TPOT) and Bayesian optimization. The performance of each workflow is quantified using different scoring metrics such as Pearson correlation (i.e., R2 correlation) and Mean Square Error (i.e., MSE). For this purpose, actual field data obtained from 1567 gas wells in Marcellus Shale, with 121 features from reservoir, drilling, completion, stimulation, and operation is tested using different proposed workflows. A proposed new hybrid workflow is then used to evaluate the type well used for evaluation of Marcellus shale gas production. In conclusion, our automated hybrid approach showed significant improvement in comparison to other proposed workflows using both scoring matrices. The new hybrid approach provides a practical tool that supports the automated model and hyperparameter selection, which is tested using real field data that can be implemented in solving different engineering problems using artificial intelligence and machine learning. The new hybrid model is tested in a real field and compared with conventional type wells developed by field engineers. It is found that the type well of the field is very close to P50 predictions of the field, which shows great success in the completion design of the field performed by field engineers. It also shows that the field average production could have been improved by 8% if shorter cluster spacing and higher proppant loading per cluster were used during the frac jobs.

Lithology and sedimentary heterogeneity of the Longmaxi Shale in the southern Sichuan Basin, China

2021 ◽  
pp. 1-49
Author(s):  
Boling Pu ◽  
Dazhong Dong ◽  
Ning Xin-jun ◽  
Shufang Wang ◽  
Yuman Wang ◽  
...  
Keyword(s):  
Continental Shelf ◽  
Deep Water ◽  
Shale Gas ◽  
Sichuan Basin ◽  
Sedimentary Environment ◽  
Gas Production ◽  
Carbonaceous Shale ◽  
Gas Wells ◽  
Longmaxi Shale ◽  
Siliceous Shale

Producers have always been eager to know the reasons for the difference in the production of different shale gas wells. The Southern Sichuan Basin in China is one of the main production zones of Longmaxi shale gas, while the shale gas production is quite different in different shale gas wells. The Longmaxi formation was deposited in a deep water shelf that had poor circulation with the open ocean, and is composed of a variety of facies that are dominated by fine-grained (clay- to silt-size) particles with a varied organic matter distribution, causing heterogeneity of the shale gas concentration. According to the different mother debris and sedimentary environment, we recognized three general sedimentary subfacies and seven lithofacies on the basis of mineralogy, sedimentary texture and structures, biota and the logging response: (1) there are graptolite-rich shale facies, siliceous shale facies, calcareous shale facies, and a small amount of argillaceous limestone facies in the deep - water shelf in the Weiyuan area and graptolite-rich shale facies and carbonaceous shale facies in the Changning area; (2) there are argillaceous shale facies and argillaceous limestone facies in the semi - deep - water continental shelf of the Weiyuan area and silty shale facies in the Changning area; (3) argillaceous shale facies are mainly developed in the shallow muddy continental shelf in the Weiyuan area, while silty shale facies mainly developed in the shallow shelf in the Changning area. Judging from the biostratigraphy of graptolite, the sedimentary environment was different in different stages.

Sliding behavior of silica ball-shale rock contact under polyacrylamide aqueous solutions

2021 ◽  
pp. 1-25
Author(s):  
Huijie Zhang ◽  
Shuhai Liu
Keyword(s):  
Adverse Effect ◽  
Shale Gas ◽  
Normal Load ◽  
Gas Production ◽  
Wear Depth ◽  
Brine Solution ◽  
Shale Rock ◽  
Different Types ◽  
The Coefficient Of Friction ◽  
Specific Speed

Abstract The tribological properties of proppant particle sliding on shale rock determine the shale gas production. This work focuses on investigating the impacts of sliding speed on the coefficient of friction (COF) and wear of the silica ball-shale rock contact, which was lubricated by water or different types of polyacrylamide (PAM) aqueous or brine solution. The experimental results show that both boundary and mixed lubrication occur under specific speed and normal load. COF and wear depth of shale rock under water are higher than those under PAM solution due to superior lubrication of PAM. COF of shale rock under PAM brine solution increases and the wear of the rock is more serious, attributed to the corrosion of shale rock and adverse effect on lubrication of PAM by brine.

New insights from shale gas production at the microscopic scale

2018 ◽  
Vol 41 (11) ◽  
Author(s):  
Natalia Kovalchuk ◽  
Constantinos Hadjistassou
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Microscopic Scale
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